Several control systems employed by vehicles, either autonomous vehicles or vehicles executing in autonomous-driving mode, predict future, safe motions, or paths, of the vehicle, both in order to avoid obstacles, such as other vehicles or pedestrians, but also to optimize some criteria associated to the operation of the vehicle. The target state can either be a fixed location, a moving location, a velocity vector, a region, or a combination thereof. The surroundings, such as road edges, pedestrians, and other vehicles, are sensed by the sensors of the vehicle and/or are at least partially known by a priori given information.
One important source of information for understanding the surroundings of a vehicle is the information sensed by the on-vehicle perception sensors, such as a camera, a stereo camera, a LIDAR, an ultrasound sensor, and radar. The objects surrounding the vehicle can be detected and recognized directly from the measurements of the on-vehicle perception sensors, as described, e.g., in U.S. Pat. No. 9,195,904. The recognized objects can be used to determine a dynamic map of the environment of the vehicle. Such a dynamic map can be used for predicting the motion of the vehicle. However, the methods for detecting and/or recognizing the object and for building the dynamic map take time and computational resources.
Therefore, it is desirable to streamline the process for determining and controlling the motion of the vehicle.